System and method for prior art analysis

ABSTRACT

Systems and methods for prior art analysis are provided. An example method comprises maintaining a patent matter database including, for at least one patent matter, a claim set or statement of invention, and a priority date. The method also includes maintaining a database of prior art documents and associating a prior art document with a first patent matter in the patent matter database. An automatic keyword analysis is performed on both the first patent matter and associated prior art document and a keyword pool is identified. Combined information is provided at a user interface information including at least identification of the first patent matter, the keyword pool, at least one keyword occurring uniquely in the first patent matter, and a timeline representing the priority date of the first patent matter and the priority or publication date of the prior art document.

RELATED APPLICATIONS

This application is a continuation of and claims the benefit of priority under 35 U.S.C. §120 to U.S. patent application Ser. No. 13/253,801, filed on Oct. 5, 2011, which claims the benefit under 35 U.S.C. 119(e) of U.S. Provisional Patent Application Ser. No. 61/542,545 filed Oct. 3, 2011, which are incorporated herein by reference in their entireties and made a part hereof.

BACKGROUND

The management of a patent portfolio involves multiple stages. Initially, a decision must be made as to what inventions are worth the investment of filing a patent application. Then, each filed patent application goes through prosecution with the patent office. Finally, for each patent that is allowed, maintenance fees must be paid at a variety of intervals to keep the patent in force.

BRIEF DESCRIPTION OF DRAWINGS

Some embodiments are illustrated by way of example and not limitation in the figures of the accompanying drawings in which:

FIG. 1 is a schematic view of computer network system 100 according to various embodiments.

FIG. 2 is a user interface, as may be used in an example embodiment.

FIG. 3 is a block diagram of a system, according to example embodiments.

FIG. 4 is a user interface, as may be used in an example embodiment.

FIG. 5 is a block diagram showing a method of analyzing prior art, according to various method embodiments.

DETAILED DESCRIPTION

The management of a patent portfolio involves multiple stages. Initially, a decision must be made as to what inventions are worth the investment of filing a patent application. Then, each filed patent application goes through prosecution with the patent office. Finally, for each patent that is allowed, maintenance fees must be paid at a variety of intervals to keep the patent in force. At each stage there are opportunities to stop spending the time and resources to obtain and maintain a patent.

In order to make knowledgeable choices the manager of the portfolio may want to know a variety of information. For example, before paying maintenance fees of an issued patent, a manager may want to know the estimated cost of the annuities over the life of the patent, whether the patent covers any current products of a company, whether the patent covers competitors patents, whether the patent is related to a licensing agreement, how influential a patent is, and what companies have been patenting recently. In a further example, before an invention disclosure or patent application is even approved for filing, a patent portfolio manager may want to assess the impact of the prior art known at that time. New prior art may also come to light later on which may affect a manager's decision to authorize subsequent annuity payments. In the fast-moving world of today, there are increasing pressures to make decisions quickly. In various embodiments, a patent portfolio and annuity management system (hereinafter also referred to as “annuity management system” or “management system”) provides tools to quickly provide information and facilitate the manager's decisions with respect to patent portfolio management.

FIG. 1 is a schematic view of computer network system 100 according to various embodiments. The computer network system 100 includes patent portfolio and annuity management system 102 and user terminal 104, communicatively coupled via network 106. In an embodiment, patent portfolio and annuity management system 102 includes web server 108, application server 110, database management server 114, which is used to manage at least operations database 116, and file server 118. Patent portfolio and annuity management system 102 may be implemented as a distributed system, for example one or more elements of the management system 102 may be located across a wide-area network from other elements of vehicle evaluation system 102. As another example, a server (e.g., web server 108, file server 118, database management server 114) may represent a group of two or more servers, cooperating with each other, provided by way of a pooled, distributed, or redundant computing model.

Network 106 may include local-area networks (LAN), wide-area networks (WAN), wireless networks (e.g., 802.11 or cellular network), the Public Switched Telephone Network (PSTN) network, ad hoc networks, personal area networks (e.g., Bluetooth) or other combinations or permutations of network protocols and network types. The network 106 may include a single local area network (LAN) or wide-area network (WAN), or combinations of LAN's or WAN's, such as the Internet. The various devices coupled to network 106 may be coupled to network 106 via one or more wired or wireless connections.

Web server 108 may communicate with file server 118 to publish or serve files stored on file server 118. Web server 108 may also communicate or interface with the application server 110 to enable web-based presentation of information. For example, application server 110 may consist of scripts, applications, or library files that provide primary or auxiliary functionality to web server 108 (e.g., multimedia, file transfer, or dynamic interface functions). In addition, application server 110 may also provide some or the entire interface for web server 108 to communicate with one or more of the other servers in the patent portfolio and annuity management system 102 (e.g., database management server 114). Web server 108, either alone or in conjunction with one or more other computers in management system 102, may provide a user-interface. The user-interface may be implemented using a variety of programming languages or programming methods, such as HTML (HyperText Markup Language), VBScript (Visual Basic® Scripting Edition), JavaScript™, XML® (Extensible Markup Language), XSLT™ (Extensible Stylesheet Language Transformations), AJAX (Asynchronous JavaScript and XML), Java™, JFC (Java™ Foundation Classes), and Swing (an Application Programming Interface for Java™).

User terminal 104 may be a personal computer or mobile device. In an embodiment, user terminal 104 includes a client program to interface with the management system 102. The client program may include commercial software, custom software, open source software, freeware, shareware, or other types of software packages. In an embodiment, the client program includes a thin client designed to provide query and data manipulation tools for a user of user terminal 104. The client program may interact with a server program hosted by, for example, application server 110. Additionally, the client program may interface with database management server 114.

Operations database 116 may be composed of one or more logical or physical databases. For example, operations database 116 may be viewed as a system of databases that when viewed as a compilation, represent an “operations database.” Sub-databases in such a configuration may include a matter database, portfolio database, user database, patent reference document or prior art database, product database, watch database, and mapping database. Operations database 116 may be implemented as a relational database, a centralized database, a distributed database, an object oriented database, or a flat database in various embodiments.

Data stored in a first database may be associated with data in a second database through the use of common data fields. For example, consider entries in the patent database formatted as [Patent ID, Patent Number] and entries in the product database formatted as [Product ID, Product Name, Patent ID]. In this manner, a product entry in the product database is associated with a patent in the patent database through the Patent ID data field. In various embodiments, a product may be associated with more than one patent by creating multiple entries in the product database, one for each patent the product is associated with. In other embodiments, one or more patent reference documents may be associated with a patent by creating multiple entries in the patent database, for example. The formats and data field titles are for illustration purposes and other names and formats may be used. Additionally, further associations between data stored in the databases may be created as discussed further herein.

During operation of patent portfolio and annuity management system 102, data from multiple data sources (internal and external) is imported into or accessed by the operations database 116. Internal sources may include data from portfolio management and annuity payment services affiliated with management system 102. External sources may include websites or databases associated with foreign and domestic patent offices, assignment databases, WIPO, and INPADOC. In various embodiments, the data is scraped and parsed from the websites if it is unavailable through a database. The data may be gathered using API calls to the sources when available. The data may be imported and stored in the operations database on a scheduled basis, such as weekly, monthly, quarterly, or some other regular or periodic interval. Alternatively, the data may be imported on-demand.

After data importation, the data may be standardized into a common format. For example, database records from internal or external sources may not be in a compatible format with the operations database. Data conditioning may include data rearrangement, normalization, filtering (e.g., removing duplicates), sorting, binning, or other operations to transform the data into a common format (e.g., using similar date formats and name formats).

FIG. 2 is an example user interface 200 of patent portfolio and annuity management system 102. User interface 200 is illustrated with multiple user interface elements. In an example embodiment, a user interface element is a graphical or textual element that a user may interact with to cause an application to perform an assigned action for the interface element. Data representing user interface 200 may be transmitted via network 106 and presented on a display of user terminal 104 through the use of a web browser. A user (e.g., manager of a patent portfolio) may interact with the user interface elements of user interface 200 through the use of an input device (e.g., stylus, cursor, mouse, finger) of the user terminal. In an embodiment, a user selection is based on the coordinates of the input device as it makes contact with the display or where a user “clicks” the mouse. The coordinates are compared to the coordinates of the user input element to determine the selection. The type of user elements, names, and layout depicted in FIG. 2 are intended to be an illustration of an example user interface of patent portfolio and annuity management system 100. Other types of user elements, names, and layouts may be used.

The user interface elements may include my matters 202, patent watches 204, company watches 206 and prior art 207. These elements may be used to select a context/view of the portfolio and annuity management system. For example, my matters lists the patents included within a portfolio of a user, patent watches lists information on patents that the user has indicated the management system is to watch, and company watches lists information on companies that the user has indicated the system should watch. Prior art 207 allows a user to perform analysis on prior art. Further details of each of these are included herein.

Date boxes 208 and 210 are user elements that allow a user to select a time period. Amount due box 112 displays the amount due with respect to annuities for patents in the portfolio of the user within the period indicated by date boxes 208 and 210. Upon activating (e.g., clicking) one of the date boxes, a user may be presented with a calendar which allows the selection of a date. Upon selecting a date, the date boxes will update to reflect the user's choice.

Drop-down menu 214 includes a list of portfolios that a user of the management system 102 is authorized to view. For example, before user interface 200 is displayed, a login screen may be presented to the user which requests a user ID and password. In various embodiments, the user ID is associated with one or more portfolios. In turn, each portfolio is associated with one or more matters. Matters may include US and foreign issued patents, pending patents, abandoned patents, and not yet filed applications. Thus, upon selection of a portfolio using drop-down menu 214, user interface 200 is populated with matters associated with the portfolio.

Checkbox 216 is an option to only display matters that currently have an annuity due. Drop-down menu 218 allows further filtering of matters. For example the matters may be filtered by US patents only, US patent applications, and foreign only.

In various embodiments, activation of button 220 updates user interface 200 to reflect the choices made by the user with respect to date boxes 208 and 210, checkbox 216, and drop-down menu 218. For example, amount due box 112 will be updated to reflect the amount due within the new period and the matters listed under column headings 222 may be filtered. In various embodiments, user interface 200 is updated as the user selections are made with respect to elements 208 to 218 without activating button 220.

FIG. 3 is a block diagram of patent portfolio and annuity management system 102, according to an example embodiment. Illustrated are user database 302, portfolio database 304, matter database 306, watch database 308, product database 310, analytics database 312, input module 314, parsing module 316, analytics module 318, display module 320, filtering module 322, and mapping module 324, and payment module 326. In various embodiments, the data stored in databases 302, 304, 306, 308, and 310 may be in the same or multiple physical locations. For example, portfolio database 304 may be located in one or more computers associated with a portfolio management service. In various embodiments, patent portfolio and annuity management system 102 may mirror databases stored in other locations. In an embodiment, when a request is made to access data stored in the databases, management system 102 determines where the data is located and directs the request to the appropriate location.

In an example embodiment user database 302 stores data representing users of patent portfolio and annuity management system 102. The data may include data fields of user credentials including a user ID and password and access rights with respect to the management system 102. The user ID may be the same as the user ID of other systems associated with management system 102. For example the user ID may be used in a portfolio management system. In this manner, access rights of the user with respect to the portfolio management system may follow to the management system 102. In various embodiments, each user ID is associated with one or more portfolio IDs. Thus, when a user logs into the management system 102, the user is presented with access to only the portfolios that have been associated with the user ID. More or fewer data fields associated with a user may be included in a user entry stored in user database 302.

Portfolio database 304, in an example embodiment, stores data representing portfolios of one or more matters. A matter may include foreign or domestic issued patents in addition to applications. Data stored in portfolio database 304 may initially have been generated in a portfolio management system and imported into patent portfolio and annuity management system 102 through the use of one or more API calls or direct access to the data in the portfolio management system. In various embodiments, a portfolio may be generated by user using the management system 102. For example, user interface may be presented to the user requesting a name in portfolio and identifiers of matters to be included in the portfolio. In an embodiment, a portfolio entry in portfolio database 304 includes data fields of portfolio ID and portfolio name. Additionally, a data field for matter ID may also be included in an entry in the portfolio database. Thus, each portfolio may be associated with one or more matters through the use of the matter ID data field. More or fewer data fields associated with a portfolio may be included in a portfolio entry of portfolio database 304.

In an embodiment, matter database 306 stores data representing matters. Each matter may be associated with one or more portfolios as well as one or more watches. In some embodiments, a matter is associated with no portfolios or watches. In an embodiment, a matter entry includes data fields representing a matter ID, title (e.g., the name of the patent or application), type of the matter (e.g., application, issued patent, PCT application), status of the matter (e.g., issued, abandoned, allowed), a link to the patent office where the matter was filed, a link to a PDF download of the matter, abstract of the matter, inventors of the matter, current owner of the matter, cited references on the face of the matter, filed date, issue date, docket number, and annuity information (e.g., due date, country, and amount due). In some embodiments, other patent reference documents or prior art in any form may be stored and associated with one or more matters. More or fewer data fields associated with a patent may be included in a matter entry stored in matter database 306. In an example embodiment, matter database 306 may store a patent matter database, wherein this database includes data about the patent matters. The data may include for at least one patent matter a claim set or statement of invention and a priority date for the claim set or statement of invention. Matter database 306 may also store a database of prior art documents (also known as “references”), wherein the prior art database includes data about the prior art documents. The data may include for at least one prior art document a priority date or publication date of the document. One or more of the prior art documents may be associated with a first patent matter in the patent matter database.

In various embodiments, a matter is associated with one or more other matters as a family with a family ID. Family members may be priority documents, continuation patents/applications, divisional patents/applications, and foreign patent/application counterparts. In an embodiment, family information is determined according to an external source such as INPADOC. Patent reference documents and/or other prior art may be manually or automatically stored, cross-cited and associated with related family matters, for example.

In an embodiment, watch database 308 stores data representing user preferences with respect to objects the user wants to track (e.g., watch). In an embodiment, an object is a company or a matter. With respect to matters, a user may indicate a preference to track the matter for any forward citations within a time period (e.g., 60 days, 3 months, etc). Thus, watch database 308 may store entries with a Watch ID that is associated with a User ID and a matter ID. With respect to companies, a user may indicate a preference to watch for publications or issued patents with a timer period. Thus, watch database 308 may store entries with a Watch ID, a user ID, and a company name. In various embodiments, the watches are user ID specific such that no matter what profile the user is viewing, the watches do not change.

In an embodiment, product database 310 stores data representing products. The products may be actual products manufactured by the user, products yet to be released, planned products, products covered in a licensing agreement, or a fictional product. In various embodiments, product database 310 stores entries with a product ID and product name which are associated with a user ID. In various embodiments, a user may tag a product as associated with a matter. Thus, an entry in the product database may also be associated with a matter ID.

In various embodiments, analytics database 312 stores data representing information on matters and companies associated with patent portfolio and annuity management system 102. This information may be organized according to an individual matter, a portfolio, a family, or company. The information may be gathered from internal or external sources of patent portfolio and annuity management system 102 or may be generated by examining the data stored in one or more databases of the management system 102.

In various embodiments, information for an individual matter may include status (e.g., disclosure received, drafting, filed, completed-waiting examination, in prosecution, allowed, issued), cited prior art, list and type of rejections (e.g., 35 U.S.C. §101, 102, 103) number of claims allowed, office action count, interviews held, IDS statements filed, attorney fees to date, and PTO fees to date. Further metrics for an individual matter stored in analytics database 312 may include, time waiting for examiner, total time in examination, time waiting for PTO while in examination, and time on appeal. Additional prosecution details formatter may include an upcoming docket dates (e.g., due dates for office action, IDS due dates, etc.). A claim prosecution history chart may also be stored in analytics database 312 for each matter. The prosecution history may include a history of claim amendments and arguments made in prosecution.

In various embodiments, analytics for an individual matter may also include data representing a claim chart. The claim chart may include one or more scope concepts on one axis and claims on the other axis. In an embodiment, a scope concept is a textual description of what a patent claim is at least limited to. Thus, if a claim comprises A, B, & C a scope concept may be A. In various embodiments, a scope concept for the claim may be broader than A because the claim will still be limited to the broader scope concept. In an embodiment, the claim charts store mappings between claims and scope concepts. The claim chart may include a variety of levels of granularity of scope concepts. Some claims may be mapped to all of the scope concepts while others may not be mapped to any scope concepts. In various embodiments, the mappings may have already been generated in a program external to the management system (e.g., a portfolio mapping system). In various embodiments, claim charts may be combined at the portfolio level. Thus, a portfolio level chart may include scope concepts for all the claims (or in some examples only the independent claims) in the portfolio.

In various embodiments, portfolio and family analytics information may be stored in analytics database 312 based on aggregating the metrics for an individual matter. In an embodiment, the analytics of a family may differ from those in a portfolio as not all family member matters may be part of a portfolio. Additionally, the analytics may be stored for multiple time periods such that comparisons may be made between metrics currently and metrics a year ago (or other time period).

Aggregated metrics may include a total patents and applications, pending and waiting for examination, in prosecution with no claims allowed, in prosecution with some claims allowed, appealed, notice of allowance received, and issued. These metrics may be compiled for both US and international matters in the portfolio. Additional information may include the international portfolio distribution by country. An age distribution of the portfolio may also be compiled. For example the portfolio may be broken down by less than one year old, 1 to 3 years old, 3 to 5 years old, 5 to 10 years old, 10 to 20 years old, and 20 or more years old. Recent filing and issue activity as well as upcoming Ford filing deadlines may be stored in analytics database 312.

In various embodiments, prosecution metrics across a portfolio or family are determined and stored in analytics database 312. This data may include matters waiting for examination, matters in examination, matters appealed, and cases allowed but not yet issued. Analytics with respect office actions may also be compiled and stored. For example success of allowance after a first office action response, a second response, etc., may be stored in analytics database 312. Additional prosecution analytics may include allowance rate (e.g., 10%) after a telephone interview, allowance after an in-person interview, percentage of interviews with response, number and type of rejection, average time in prosecution (e.g., in months), average time to file a response, and average time to next office action. Further, the list of recently allowed cases, recently appeal cases, stalled cases, and recently abandoned cases may also be stored for each portfolio and family in analytics database 312.

In various embodiments, data stored in the database for group of matters in a portfolio or family is analyzed to determine the top (e.g., ten) most cited patents, the top most cited inventors, top most cited prior art owners (e.g., according to assignment documents or the face of the patent), newly (e.g., within the last 60 days) cited prior art owners, and top most cited prior art inventors. This information may be stored in analytics database 312.

In various embodiments, annuity cost information regarding cost projections for both US issued patents and international patents may also be stored. Upcoming foreign filing deadlines with respect to annuities may also be stored in analytics database 312.

In various embodiments, the results of keyword analysis on one or more matters and/or prior art references may be stored in analytics database 312. The keyword analysis may be based on the occurrences of the keywords in the matter or references to derive a score or keyword overlap.

In various embodiments, input module 314 receives data from multiple sources where it may be further processed by one or more other modules and stored in one or more of databases 302-312. For example, input module 314 may be configured to utilize one or more APIs to data from one or more patent data stores (e.g., public PAIR, private PAIR, INPADOC, foreign patent offices, patent docketing systems, portfolio management systems, etc). The data may include published patent documents, patent applications, office actions or other patent office correspondence, prior art references, claim mappings, dockets dates, and annuity payment data.

In various embodiments, input module 314 is configured to receive input from one or more user interface elements. For example, the management system 102 may present multiple user interfaces to users. These user interfaces may enable users to input data directly into databases 302-312, instruct the management system to retrieve data from patent data stores, and instruct the management system to perform various operations on the data in databases 302-312.

Additionally, input module 314 may be configured to determine the selection of one or more user interface elements by a user and initiate the action associated with the selected user interface element. For example user interface element may include a drop-down menu to select a portfolio. Input module 314 may be configured to receive a selection of the portfolio and a drop-down menu. Then, input module 314 may pass the selection to one or more other modules for further processing. For example, display module 320 may update the drop-down menu to indicate the selection of a portfolio.

In various embodiments, parsing module 316 takes the data that has initially been inputted by input module 314 and formats it according to the data fields of databases 302-312 as discussed above. For example, consider a patent publication that is been inputted by input module 314. Parsing module 316 may use a combination of automatic image recognition and text analysis to determine the filing date, issue date, title, abstract, and claims of the patent. In some embodiments, parsing module 316 may flag certain pieces of data that had been determined to be potentially inaccurate (e.g., a number could not be read). A user of management system 102 may then examine the flagged data and manually enter in the information.

The resulting data that has been parsed by parsing module 316 may then be entered as an entry in one or more of databases 302-312. This may be accomplished by, for example, formulating an SQL query with the parsed information. In various embodiments parsing module 316 may parse multiple piece of information before generating a database entry. For example, input module 314 may receive a docket number for an issued patent. The docket number may be combined with the information parse from the issued patent to form an entry in matter database 306.

In various embodiments, analytics module 318 is configured to examine and run calculations on the data stored in the databases 302-312 to generate the analytics discussed previously. For example, analytics module 318 may formulate an SQL query that retrieves the number of times that a prior art reference has been cited within a portfolio. This query may be run for each prior art cited within the portfolio to determine a list of the most cited (e.g., the top ten) prior art references with a portfolio. In an embodiment, the queries are formulated and run as requested by a user. In an embodiment, once the analytics information has been determined it is stored within analytics database 312. In various embodiments, queries are formulated and run on a period basis (e.g., nightly) and entries in analytics database 312 may be updated to reflect any changes.

In various embodiments, the analytics module 318 is configured to receive input identifying a pool of keywords for a first patent matter in matter database 306 and associated prior art documents in matter database 306. The term keyword is intended to include individual keywords as well as a number of keywords grouped together making up a key phrase, for example. The module 318 may be further configured to perform a keyword analysis on the first patent matter and associated prior art documents based on occurrences of the keywords in the first patent matter and associated prior art documents. The module 318 may be further configured to identify, based on the analysis, keywords occurring uniquely in the first patent matter. In view of their uniquely occurring nature, these keywords may be regarded as claim elements potentially differentiating the claim set or statement of invention over the disclosures contained in the one or more prior art documents.

The analytics module 318 may be further configured to perform the keyword analysis automatically on the first patent matter and the one or more prior art documents simultaneously. Prior art button 207 shown in FIG. 2 may be selected by a portfolio manager to enter further user displays and start the automatic keyword analysis. The analytics module may be further configured to receive synonyms of the keywords to add to the pool of identified keywords. In this way, the keyword analysis may be enhanced.

The analytics module 318 may be further configured to automatically rank the prior art documents based on the degree of differentiation between the first patent matter and the one or more prior art documents, based on the keyword analysis. The analytics module may be further configured to rank the prior art document with the highest degree of differentiation as lowest ranked in potential relevance to the claim set or statement of invention of the first patent matter. Similarly, the analytics module may be further configured to rank the prior art document with the lowest degree of differentiation as highest ranked in potential relevance to the claim set or statement of invention of the first patent matter.

The analytics module 318 may be further configured to derive a keyword differentiation score, based on the keyword analysis, for the one or more prior art documents. The analytics module may be further configured to derive a keyword overlap score, based on the keyword analysis, for the one or more prior art documents.

The analytics module 318 may be further configured to identify the cited inventors or assignees of the prior art documents and automatically rank the prior art documents by inventor or assignee having the most keywords occurring in one or more of the prior art documents.

In an embodiment, display module 320 is configured to display user interfaces and information retrieved from one or more databases 302-312. For example display module 320 may generate user interface 200 of FIG. 2. If a user is accessing management system 102 remotely (e.g., through a web browser) display module 320 may be configured to transmit data representing a user-interface through a network to a user terminal. In various embodiments, display module 320 is configured to generate one or more charts of data stored in databases 302-312. For example, display module 320 may generate a pie chart of the top 10 inventors within a portfolio.

With reference to the keyword analysis described above, display module 320 may be configured to display a user interface wherein the display module is further configured to visually present the ranking of the one or more prior art documents in the user interface. The display module 320 may be further configured to provide, in the user interface, a visual indication of the ranking in a time line.

The display module 320 may be further configured to visually provide, in the user interface, a time line representing the priority date of the first patent matter, and the priority or publication dates of the or each prior art document. The display module may be further configured to provide a visual indication of the degree of differentiation of the one or more prior documents in the time line.

The display module 320 may be further configured to provide, in the user interface, a visual indication of the technology class and/or subclass of the first patent matter and the one or more prior art documents. In an example embodiment, the display module may be further configured to provide, in the user interface, a time line or chart indicating when one or more of the identified keywords first appeared in one or more of the prior art documents.

In various embodiments, filtering module 322 is configured to filter a set of matters according to a user preference. For example, a user may activate a check box that indicates only pending matters should be shown in a user interface. Filtering module 322 may formulate a query consistent with retrieving only pending matters. The results of the query may then be shared with display module 320 where the user interface may be updated.

In various embodiments, mapping module 324 is configured to receive or generate mappings from a product to a matter. This may be accomplished, for example, by receiving a selection of a product by user and a matter by the user. In various embodiments, mapping module 324 is configured to present an automated mapping of the product to a matter for user to confirm or deny. For example, mapping module 324 may present a claim chart for an issued patent to a user. As discussed, the claim chart includes one or more scope concepts that one or more the claims of the patent are limited to. In conjunction with input module 314, mapping module 324, may receive selections of the user of one or more of the scope concepts that are potentially affiliated with the product. Thus, a comparison may be made between what the claims are limited to and what the product may be. For example, if a product, as defined by the selection of one or more scope concepts by the user, is affiliated toward scope concepts A, B, and C and claim 1 of the patent has been mapped to scope concepts A, B, and C, the mapping module 324 may present an option to map the product to the patent. In various embodiments the user may override this recommendation and select to not map the product to the patent. Similarly, a user may indicate that a product is affiliated with the patent even if the scope concepts do not match.

In various embodiments, the mapping module 324 is configured to receive or generate mappings from prior art to a matter. This may be accomplished, for example, by receiving a selection of prior art and a matter by the user. The selection of the prior art may be based on cited references or though other external prior art search. The selections may be conducted manually by a user, or automatically by analytics module 318, for example. In various embodiments, mapping module 324 is configured to present an automated mapping of the prior art to a matter for user to review. In various embodiments, the mapping module can be configured to carry out any of the keyword analysis described above in relation to analytics module 318.

In an embodiment, once the product or prior art mapping information has been determined it is stored within analytics database 312 or matter database 306. In various embodiments, queries are formulated and run on a period basis (e.g., nightly) and entries in analytics database 312 or matter database 306 may be updated to reflect any changes.

In various embodiments, payment module 326 is configured to receive selections by the user of which annuities to pay for matters in a portfolio. Additionally, payment module 326 may receive user preferences related to the payment of the annuities. Payment module 326 may receive payment information from a user and forward the payment information to the appropriate agency/office. In some embodiments, the annuity management system 102 organizes payment of the annuity on behalf of the user and the user pays annuity management system 102.

Some embodiments of the present inventive subject matter include methods for electronic analysis of prior art in a patent portfolio and annuity management system 102. One such embodiment is illustrated in FIG. 4. In some embodiments, method 400 includes maintaining a patent matter database 402 wherein the database includes data about the patent matters. The data may include for at least one patent matter a claim set or statement of invention and a priority date for the claim set or statement of invention. The method may further comprise maintaining a database of prior art documents 404 wherein the prior art database includes data about the prior art documents. In some embodiments, the data may include for at least one prior art document a priority date or publication date of the document. The method 400 may further comprise associating one or more prior art documents with a first patent matter in the patent matter database 406 and identifying a pool of keywords for the first patent matter and associated prior art documents 408. The method may further comprise performing a keyword analysis on the first patent matter and associated prior art documents based on occurrences of the keywords in the first patent matter and associated prior art documents 410. The method may further comprise identifying, based on the analysis, keywords occurring uniquely in the first patent matter as potential claim elements differentiating the claim set or statement of invention over the disclosures contained in the one or more prior art documents 412.

In some embodiments of method 300, the keyword analysis may be performed automatically on the first patent matter and the one or more prior art documents simultaneously. The method may further comprise manually adding synonyms of the keywords to the pool of identified keywords.

Further example embodiments of the method may comprise automatically ranking the prior art documents based on the degree of differentiation between the first patent matter and the one or more prior art documents. The prior art document with the highest degree of differentiation may be lowest ranked in potential relevance to the claim set or statement of invention of the first patent matter. The prior art document with the lowest degree of differentiation may be highest ranked in potential relevance to the claim set or statement of invention of the first patent matter.

In yet further embodiments of the method 300, the method may further comprise deriving a keyword differentiation score, based on the keyword analysis, for the one or more prior art documents. The method may further comprise deriving a keyword overlap score, based on the keyword analysis, for the one or more prior art documents.

In further example embodiments, the method may further comprise visually presenting the ranking of the one or more prior art documents in a graphic user interface. The method may further comprise providing, in the graphic user interface, a visual indication of the ranking in a time line. The method may yet further comprise visually providing, in a graphic user interface, a time line representing the priority date of the first patent matter, and the priority or publication dates of the or each prior art document. A visual indication of the degree of differentiation of the one or more prior art documents may be provided in the time line. The method may further comprise providing, in a graphic user interface, a visual indication of the technology class and/or subclass of the first patent matter and the one or more prior art document. The method may yet further comprise providing, in a graphic user interface, a time line or chart indicating when one or more of the identified keywords first appeared in one or more of the prior art documents.

In some example embodiments, the method may further comprising identifying the cited inventors or assignees (referred to as “Owner” in FIG. 5 below) of the prior art documents and automatically ranking the prior art documents by inventor or assignee having the most keywords occurring in one or more of the prior art documents.

Reference is now made to FIG. 5 which shows a user interface 500 which may be used to facilitate the methods of the present inventive subject matter, according to example embodiments. The user interface 500 may be displayed by display module 320 described above. The user interface may be provided in a computer monitor or mobile device. The type of user elements, names, and layout depicted in FIG. 5 are intended to be an illustration of an example user interface of patent portfolio and annuity management system 100. Other types of user elements, names, and layouts may be used.

Shown at element 502 is the identification of a first patent matter in the patent matter database stored in matter database 306. Associated with the patent matter, either automatically by the system 102 or manually by a portfolio manager for example, are one or more prior art documents stored in a prior art database also contained, in this example embodiment, in the matter database 302. The identity of these prior art documents is shown in user element 504. The prior art documents may be sourced through citation by a patent office or by a patentability search conducted by a portfolio manager, for example.

A pool of keywords is shown in user element 506. The keywords may be manually selected by a portfolio manager, for example, or generated automatically by the system 102. Synonyms of the keywords may be entered manually at element 508 so that the keyword analysis described in method 400 above may be enhanced and, if necessary, performed again by selecting user element 510 marked “Run”. The keywords may be used to perform a keyword analysis in accordance with any one or more of the method embodiments or systems described above.

In some example embodiments, once the keyword analysis has been performed, the prior art documents are ranked based on their degree of differentiation from patent matter in element 502 as shown by arrow 512. The most relevant prior art document (i.e., with the most occurrences of a given keyword present in the patent matter 502) may be shown at the top of the ranking list in element 504, while less relevant prior art documents (i.e., with fewer occurrences of such keywords) may follow further down in the list. The ranking order may be reversed. Each prior art document may be accorded a keyword differentiation or keyword overlap score as shown at 513. In this way, a portfolio manager seeking to make an informed decision about whether to file or renew a given patent matter can quickly ascertain the potential relevance of prior art impacting the claim set or statement of invention in patent matter 502 under review.

In yet further example embodiments, a time line may be provided as shown at user element 514. The time line may run from a given date in the further past, as shown for example at 516, to a more recent date as shown for example at 518. Spread along the timeline 514, in accordance with their priority or publication dates, are the respective prior art documents listed in element 504. User elements 520 may be used to display details of the prior art documents, such as the differentiation or overlap scores, the prior art owner (assignee or inventors), and the keywords occurring in the respective prior art documents. A user element 522 may be provided to display similar details for the patent matter, including for example the identity of keywords (in the illustrated example “xxx”) not found in any of the prior art documents. A similar conclusion may be presented in element 524.

In yet further example embodiments, pie charts 526 and 528 may be displayed illustrating, for example, the number of occurrences of keywords in the prior art (as shown in 526) or the extent to which the various owners of the prior art own the more relevant prior art documents (in 528).

Modules, Components and Logic

Certain embodiments are described herein as including logic or a number of components, modules, or mechanisms. Modules may constitute either software modules (e.g., code embodied (1) on a non-transitory machine-readable medium or (2) in a transmission signal) or hardware-implemented modules. A hardware-implemented module is tangible unit capable of performing certain operations and may be configured or arranged in a certain manner. In example embodiments, one or more computer systems (e.g., a standalone, client or server computer system) or one or more processors may be configured by software (e.g., an application or application portion) as a hardware-implemented module that operates to perform certain operations as described herein.

In various embodiments, a hardware-implemented module may be implemented mechanically or electronically. For example, a hardware-implemented module may comprise dedicated circuitry or logic that is permanently configured (e.g., as a special-purpose processor, such as a field programmable gate array (FPGA) or an application-specific integrated circuit (ASIC)) to perform certain operations. A hardware-implemented module may also comprise programmable logic or circuitry (e.g., as encompassed within a general-purpose processor or other programmable processor) that is temporarily configured by software to perform certain operations. It will be appreciated that the decision to implement a hardware-implemented module mechanically, in dedicated and permanently configured circuitry, or in temporarily configured circuitry (e.g., configured by software) may be driven by cost and time considerations.

Accordingly, the term “hardware-implemented module” should be understood to encompass a tangible entity, be that an entity that is physically constructed, permanently configured (e.g., hardwired) or temporarily or transitorily configured (e.g., programmed) to operate in a certain manner and/or to perform certain operations described herein. Considering embodiments in which hardware-implemented modules are temporarily configured (e.g., programmed), each of the hardware-implemented modules need not be configured or instantiated at any one instance in time. For example, where the hardware-implemented modules comprise a general-purpose processor configured using software, the general-purpose processor may be configured as respective different hardware-implemented modules at different times. Software may accordingly configure a processor, for example, to constitute a particular hardware-implemented module at one instance of time and to constitute a different hardware-implemented module at a different instance of time.

Hardware-implemented modules can provide information to, and receive information from, other hardware-implemented modules. Accordingly, the described hardware-implemented modules may be regarded as being communicatively coupled. Where multiple of such hardware-implemented modules exist contemporaneously, communications may be achieved through signal transmission (e.g., over appropriate circuits and buses) that connect the hardware-implemented modules. In embodiments in which multiple hardware-implemented modules are configured or instantiated at different times, communications between such hardware-implemented modules may be achieved, for example, through the storage and retrieval of information in memory structures to which the multiple hardware-implemented modules have access. For example, one hardware-implemented module may perform an operation, and store the output of that operation in a memory device to which it is communicatively coupled. A further hardware-implemented module may then, at a later time, access the memory device to retrieve and process the stored output. Hardware-implemented modules may also initiate communications with input or output devices, and can operate on a resource (e.g., a collection of information).

The various operations of example methods described herein may be performed, at least partially, by one or more processors that are temporarily configured (e.g., by software) or permanently configured to perform the relevant operations. Whether temporarily or permanently configured, such processors may constitute processor-implemented modules that operate to perform one or more operations or functions. The modules referred to herein may, in some example embodiments, comprise processor-implemented modules.

Similarly, the methods described herein may be at least partially processor-implemented. For example, at least some of the operations of a method may be performed by one or processors or processor-implemented modules. The performance of certain of the operations may be distributed among the one or more processors, not only residing within a single machine, but deployed across a number of machines. In some example embodiments, the processor or processors may be located in a single location (e.g., within a home environment, an office environment or as a server farm), while in other embodiments the processors may be distributed across a number of locations.

The one or more processors may also operate to support performance of the relevant operations in a “cloud computing” environment or as a “software as a service” (SaaS). For example, at least some of the operations may be performed by a group of computers (as examples of machines including processors), these operations being accessible via a network (e.g., the Internet) and via one or more appropriate interfaces (e.g., Application Program Interfaces (APIs).)

Electronic Apparatus and System

Example embodiments may be implemented in digital electronic circuitry, or in computer hardware, firmware, software, or in combinations of them. Example embodiments may be implemented using a computer program product, e.g., a computer program tangibly embodied in an information carrier, e.g., in a machine-readable medium for execution by, or to control the operation of, data processing apparatus, e.g., a programmable processor, a computer, or multiple computers.

A computer program can be written in any form of programming language, including compiled or interpreted languages, and it can be deployed in any form, including as a stand-alone program or as a module, subroutine, or other unit suitable for use in a computing environment. A computer program can be deployed to be executed on one computer or on multiple computers at one site or distributed across multiple sites and interconnected by a communication network.

In example embodiments, operations may be performed by one or more programmable processors executing a computer program to perform functions by operating on input data and generating output. Method operations can also be performed by, and apparatus of example embodiments may be implemented as, special purpose logic circuitry, e.g., a field programmable gate array (FPGA) or an application-specific integrated circuit (ASIC).

The computing system can include clients and servers. A client and server are generally remote from each other and typically interact through a communication network. The relationship of client and server arises by virtue of computer programs running on the respective computers and having a client-server relationship to each other. In embodiments deploying a programmable computing system, it will be appreciated that that both hardware and software architectures require consideration. Specifically, it will be appreciated that the choice of whether to implement certain functionality in permanently configured hardware (e.g., an ASIC), in temporarily configured hardware (e.g., a combination of software and a programmable processor), or a combination of permanently and temporarily configured hardware may be a design choice. Below are set out hardware (e.g., machine) and software architectures that may be deployed, in various example embodiments.

Example Machine Architecture and Machine-Readable Medium

In some example embodiments, a machine is shown in the example form of a computer system 102 within which instructions, for causing the machine to perform any one or more of the methodologies discussed herein, may be executed. In alternative embodiments, the machine operates as a standalone device or may be connected (e.g., networked) to other machines. In a networked deployment, the machine may operate in the capacity of a server or a client machine in server-client network environment, or as a peer machine in a peer-to-peer (or distributed) network environment. The machine may be a personal computer (PC), a tablet PC, a set-top box (STB), a Personal Digital Assistant (PDA), a cellular telephone, a web appliance, a network router, switch or bridge, or any machine capable of executing instructions (sequential or otherwise) that specify actions to be taken by that machine. Further, while only a single machine is illustrated, the term “machine” shall also be taken to include any collection of machines that individually or jointly execute a set (or multiple sets) of instructions to perform any one or more of the methodologies discussed herein.

The example computer system 102 may include a processor (e.g., a central processing unit (CPU), a graphics processing unit (GPU) or both), a main memory and a static memory, which communicate with each other via a bus. The computer system 102 may further include a video display unit (e.g., a liquid crystal display (LCD) or a cathode ray tube (CRT)). The computer system 102 may also include an alphanumeric input device (e.g., a keyboard), a user interface (UI) navigation device (e.g., a mouse), a disk drive unit, a signal generation device (e.g., a speaker) and a network interface device.

Machine-Readable Medium

The term “machine-readable medium” may include a single medium or multiple media (e.g., a centralized or distributed database, and/or associated caches and servers) that store the one or more instructions or data structures. The term “machine-readable medium” shall also be taken to include any tangible medium that is capable of storing, encoding or carrying instructions for execution by the machine and that cause the machine to perform any one or more of the methodologies of the present invention, or that is capable of storing, encoding or carrying data structures utilized by or associated with such instructions. The term “machine-readable medium” shall accordingly be taken to include, but not be limited to, solid-state memories, and optical and magnetic media. Specific examples of machine-readable media include non-volatile memory, including by way of example semiconductor memory devices, e.g., Erasable Programmable Read-Only Memory (EPROM), Electrically Erasable Programmable Read-Only Memory (EEPROM), and flash memory devices; magnetic disks such as internal hard disks and removable disks; magneto-optical disks; and CD-ROM and DVD-ROM disks.

Transmission Medium

The term “transmission medium” shall be taken to include any intangible medium that is capable of storing, encoding or carrying instructions for execution by the machine, and includes digital or analog communications signals or other intangible media to facilitate communication of such software.

Although an embodiment has been described with reference to specific example embodiments, it will be evident that various modifications and changes may be made to these embodiments without departing from the broader spirit and scope of the invention. Accordingly, the specification and drawings are to be regarded in an illustrative rather than a restrictive sense. The accompanying drawings that form a part hereof, show by way of illustration, and not of limitation, specific embodiments in which the subject matter may be practiced. The embodiments illustrated are described in sufficient detail to enable those skilled in the art to practice the teachings disclosed herein. Other embodiments may be utilized and derived therefrom, such that structural and logical substitutions and changes may be made without departing from the scope of this disclosure. This Detailed Description, therefore, is not to be taken in a limiting sense, and the scope of various embodiments is defined only by the appended claims, along with the full range of equivalents to which such claims are entitled.

Such embodiments of the inventive subject matter may be referred to herein, individually and/or collectively, by the term “invention” merely for convenience and without intending to voluntarily limit the scope of this application to any single invention or inventive concept if more than one is in fact disclosed. Thus, although specific embodiments have been illustrated and described herein, it should be appreciated that any arrangement calculated to achieve the same purpose may be substituted for the specific embodiments shown. This disclosure is intended to cover any and all adaptations or variations of various embodiments. Combinations of the above embodiments, and other embodiments not specifically described herein, will be apparent to those of skill in the art upon reviewing the above description.

Abstract

The Abstract of the Disclosure is provided to comply with 37 C.F.R. §1.72(b), requiring an abstract that will allow the reader to quickly ascertain the nature of the technical disclosure. It is submitted with the understanding that it will not be used to interpret or limit the scope or meaning of the claims. In addition, in the foregoing Detailed Description, it can be seen that various features are grouped together in a single embodiment for the purpose of streamlining the disclosure. This method of disclosure is not to be interpreted as reflecting an intention that the claimed embodiments require more features than are expressly recited in each claim. Rather, as the following claims reflect, inventive subject matter lies in less than all features of a single disclosed embodiment. Thus the following claims are hereby incorporated into the Detailed Description, with each claim standing on its own as a separate embodiment. 

What is claimed is:
 1. A method comprising: maintaining a patent matter database, the database including data about the patent matters, the data including for at least one patent matter: a claim set or statement of invention, and a priority date for the claim set or statement of invention; maintaining a database of prior art documents, wherein the prior art database includes data about the prior art documents; associating a prior art document with a first patent matter in the patent matter database; performing an automatic keyword analysis on both the first patent matter and associated prior art document, and automatically identifying a keyword pool for the first patent matter and prior art document based on occurrences of one or more keywords in the first patent matter and associated prior art document; automatically identifying, based on the analysis, at least one keyword occurring uniquely in the first patent matter; and combining at a user interface information including at least identification of the first patent matter, the keyword pool, the at least one keyword occurring uniquely in the first patent matter, and a timeline representing the priority date of the first patent matter and the priority or publication date of the prior art document.
 2. The method of claim 1, further comprising adding synonyms of the keywords to the keyword pool.
 3. The method of claim 1, further comprising automatically ranking the prior art document based on a degree of differentiation between the first patent matter and the prior art document.
 4. The method of claim 3, wherein a prior art document with a highest degree of differentiation is lowest ranked in potential relevance to the claim set or statement of invention of the at least one patent matter.
 5. The method of claim 3, wherein a prior art document with a lowest degree of differentiation is highest ranked in potential relevance to the claim set or statement of invention of the at least one patent matter.
 6. The method of claim 3, further comprising visually presenting the ranking of the prior art document in the user interface.
 7. The method of claim 6, further comprising providing, in the user interface, a visual indication of the ranking in association with the time line.
 8. The method of claim 1, further comprising providing, in the user interface, a visual indication of the technology class and/or subclass of the first patent matter and the prior art document.
 9. The method of claim 1, further comprising providing, in the user interface, an indication on the time line of when one or more of the keywords in the keyword pool first appeared in a set of prior art documents.
 10. The method of claim 1, further comprising identifying a cited inventor or assignee of the prior art document and automatically ranking the prior art document by inventor or assignee having the most keywords occurring in the prior art document.
 11. A patent portfolio management system, the system comprising: a patent matter database, wherein the database includes data about the patent matters, the data including for at least one patent matter: a claim set or statement of invention, and a priority date for the claim set or statement of invention; a database of prior art documents, wherein the prior art database includes data about the prior art documents; a hardware-implemented analytics module including at least one processor to: associate a prior art document with a first patent matter in the patent matter database; perform an automatic keyword analysis on both the first patent matter and associated prior art document and automatically identify a keyword pool for the first patent matter and associated prior art document based on occurrences of one or more keywords in the first patent matter and associated prior art document; automatically identify, based on the analysis, at least one keyword occurring uniquely in the first patent matter; and combine at a user interface information including at least identification of the first patent matter, the keyword pool, the at least one keyword occurring uniquely in the first patent matter, and a timeline representing the priority date of the first patent matter and the priority or publication date of the prior art document.
 12. The system of claim 11, wherein the analytics module is further to include synonyms of the keywords in the keyword pool.
 13. The system of claim 11, wherein the analytics module is further automatically to rank the prior art document based on a degree of differentiation between the first patent matter and the prior art document.
 14. The system of claim 13, wherein the analytics module is further to rank a prior art document with the highest degree of differentiation as lowest ranked in potential relevance to the claim set or statement of invention of the at least one patent matter.
 15. The system of claim 13, wherein the analytics module is further to rank a prior art document with the lowest degree of differentiation as highest ranked in potential relevance to the claim set or statement of invention of the at least one patent matter.
 16. The system of claim 13, further comprising a display module to display a user interface, wherein the display module is further to visually present the ranking of the prior art document in the user interface.
 17. The system of claim 16, wherein the display module is further to provide, in the user interface, a visual indication of the ranking in association with the time line.
 18. The system of claim 16, wherein the display module is further to provide a visual indication of the degree of differentiation of the prior document in association with the time line.
 19. The system of claim 16, wherein the display module is further to provide, in the user interface, a visual indication of the technology class and/or subclass of the first patent matter and the prior art document.
 20. The system of claim 16, wherein the display module is further to provide, in the user interface, an indication on the time line of when one or more of the keywords in the keyword pool first appeared in a set of prior art documents. 